As Onboard Informatics continues to be “the” data provider for publishers, we are proud to be the unsung heroes of the success of this year’s latest and greatest place to reside story.
But how do we go about selecting places to be highlighted by our publisher clients? Well when we aren’t throwing darts at a big map of the United States, while counting our bribe money for letting Gary, Indiana on the list we actually use very exact methodologies that produce the best results possible…

I want to give you a very high level over view of how the process goes; I don’t want to be too specific as to not reveal our secret sauce (As much as I wish, it is not Thousand Islands dressing… L)

So our hypothetical magazine will be Murph Digest, and they want to do a story that will highlight the Best Big City to Live.

In the very beginning of the process is where we unfortunately start to alienate some really great places to live. Sorry Gary, Indiana next year will be your year... But in all seriousness, good screening criteria are vital! It will ensure that the places selected truly represent the focus of the story.. Because our hypothetical story will center on large cities, we will establish a population threshold that Murph Digest considers large enough to consider that place a “big” city. So every city that is left will at least meet the bare minimum in the population field.

Now that we are only left with places that qualify as "big" cities, we can proceed to the next step. While working with the client, we identify what data points they are interested in for their story. We want to know who their readers are and what are their readers are interested in, i.e what market are they targeting. Onboard Informatics experience and expertise is invaluable during this part of the process. Besides the obvious data, we have data on some of the most outlandish things and methodologies for aggregating it that never cease to amaze our clients. So for Murph Digest, low crime rates and the number of divorced women are the only two fields that they are interested in.

After gathering the crime rate data and the number of divorced women for all the places that qualify as a “big” city, we can rank the places. Getting input from the client, we select the best weighting technique (lots of secret sauce here), and we can send over a simple spreadsheet to the client with the data filtered ahead of time. Once the spreadsheet is in the client’s hands, they can play with the weights and base their decisions on their own preferences; and apparently low crime is only worth 10% and the number of divorced women is worth 90% to Murph Digest. I guess their readers are cougar hunters!!!